本論文旨在尋找一可行之自主型水下載具障礙物避碰方法，並探討其在不同環境因素底下經模糊控制系統之操控後所表現出的避碰性能，首先以PMM(Planar Motion Mechanism)試驗尋找AUV之流體動力係數供動態數值模擬程式來進行六度運動模擬，以做為開發控制系統的平台，為快速開發控制系統，試以自調式模糊控制器來進行AUV的運動操控。
障礙物避碰方法使用水下影像偵測之模擬，將影像區分為七個區塊做為七個待選航向，並利用BK三角副乘積將七個待選航向之安全程度與前往路徑點之效率做運算以即時判斷出最佳航向。
數值模擬中以四種不同障礙物地形來做為AUV障礙物避碰性能模擬的平台，首先討論自調式模糊控制與靜態模糊控制之表現差異，又針對不同的水下能見度與不同的安全程度設定來做避碰性能之比較，再加入外界干擾探討AUV在洋流中的避碰性能與可控性，最後則獨立探討當AUV在進行垂向避碰時之表現。結果顯示利用此避碰方法使AUV在靜水中能夠以足夠的安全距離通過行徑路線上的障礙物，研究結果將提供給實際水下影像偵測障礙物避碰做為一參考方法。

The purpose of the thesis is to develop an autonomous underwater vehicle (AUV) with obstacle-avoidance function. The performance of anti-collision using the fuzzy controller in the different ocean environment is studied. The PMM (Planar Motion Mechanism) test is applied to obtain the related hydrodynamic coefficients in order to investigate the six degrees of freedom of motions, which serves as the platform for developing the control system. In order to quickly develop the system, the self-tuning fuzzy controller is adopted in the AUV motion steering.
The underwater image detection simulation is used as the tool for the obstacle avoidance. The image token by the camera is partitioned into seven sections which represent different candidate heading angle. Using the fuzzy relation of BK Triangle Sub-product to calculate the relationship between safety degree and route accuracy, then select the successive optimal heading for the AUV avoid obstacle.
In the numerical simulations, four types of obstacle maps are selected as the platform to investigate the anti-collision steering performance. Fist, the difference between the self-tuning fuzzy controller and the static one is compared and the different underwater visibility and safety set are then discussed. The effects of current on the anti-collision performance and the control performance are also investigated. Finally, we independently study the performance to avoid obstacle by vertical motion. The results reveal that AUV can achieve the mission with enough safe distance in calm water. The present study can offer the useful information to the AUV obstacle-avoidance reference while applying the underwater image detection method.

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